{"total":40,"rows":[{"id":"2205.12548","title":"RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning","created":"2022-05-25","cited_by_count":366,"area":null},{"id":"2107.12808","title":"Open-Ended Learning Leads to Generally Capable Agents","created":"2021-07-27","cited_by_count":182,"area":null},{"id":"2103.04551","title":"Behavior From the Void: Unsupervised Active Pre-Training","created":"2021-03-08","cited_by_count":174,"area":null},{"id":"2107.14171","title":"Tianshou: a Highly Modularized Deep Reinforcement Learning Library","created":"2021-07-29","cited_by_count":143,"area":null},{"id":"2107.00644","title":"Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation","created":"2021-07-01","cited_by_count":105,"area":null},{"id":"2201.04122","title":"In Defense of the Unitary Scalarization for Deep Multi-Task Learning","created":"2022-01-11","cited_by_count":67,"area":null},{"id":"2104.06159","title":"Muesli: Combining Improvements in Policy Optimization","created":"2021-04-13","cited_by_count":53,"area":null},{"id":"2310.09971","title":"AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents","created":"2023-10-15","cited_by_count":41,"area":null},{"id":"2305.03286","title":"Composite Motion Learning with Task Control","created":"2023-05-05","cited_by_count":28,"area":null},{"id":"2105.05347","title":"Return-based Scaling: Yet Another Normalisation Trick for Deep RL","created":"2021-05-11","cited_by_count":23,"area":null},{"id":"2107.05431","title":"CoBERL: Contrastive BERT for Reinforcement Learning","created":"2021-07-12","cited_by_count":21,"area":null},{"id":"2310.08348","title":"LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios","created":"2023-10-12","cited_by_count":20,"area":null},{"id":"2205.14205","title":"ALMA: Hierarchical Learning for Composite Multi-Agent Tasks","created":"2022-05-27","cited_by_count":18,"area":null},{"id":"2103.10369","title":"Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning","created":"2021-03-18","cited_by_count":14,"area":null},{"id":"2204.00656","title":"Consistency driven Sequential Transformers Attention Model for Partially Observable Scenes","created":"2022-04-01","cited_by_count":11,"area":null},{"id":"2509.11481","title":"RAPTOR: A Foundation Policy for Quadrotor Control","created":"2025-09-15","cited_by_count":8,"area":null},{"id":"2310.17805","title":"Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks","created":"2023-10-26","cited_by_count":7,"area":null},{"id":"2311.11557","title":"Replay-enhanced Continual Reinforcement Learning","created":"2023-11-20","cited_by_count":7,"area":null},{"id":"2202.11664","title":"Comparative analysis of machine learning methods for active flow control","created":"2022-02-23","cited_by_count":6,"area":null},{"id":"2204.10256","title":"Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach","created":"2022-04-21","cited_by_count":6,"area":null},{"id":"2302.02182","title":"Online Reinforcement Learning in Non-Stationary Context-Driven Environments","created":"2023-02-04","cited_by_count":6,"area":null},{"id":"2311.15594","title":"Networked Multiagent Safe Reinforcement Learning for Low-carbon Demand Management in Distribution Network","created":"2023-11-27","cited_by_count":4,"area":null},{"id":"2102.09361","title":"Efficient Reinforcement Learning in Resource Allocation Problems Through Permutation Invariant Multi-task Learning","created":"2021-02-18","cited_by_count":3,"area":null},{"id":"2104.12895","title":"Computational Performance of Deep Reinforcement Learning to find Nash Equilibria","created":"2021-04-26","cited_by_count":3,"area":null},{"id":"2104.14138","title":"Adapting to Reward Progressivity via Spectral Reinforcement Learning","created":"2021-04-29","cited_by_count":3,"area":null},{"id":"2112.01765","title":"Learning Emergent Random Access Protocol for LEO Satellite Networks","created":"2021-12-03","cited_by_count":3,"area":null},{"id":"2306.04403","title":"Policy-Based Self-Competition for Planning Problems","created":"2023-06-07","cited_by_count":3,"area":null},{"id":"2101.02663","title":"L2PF -- Learning to Prune Faster","created":"2021-01-07","cited_by_count":2,"area":null},{"id":"2201.05560","title":"Demystifying Reinforcement Learning in Time-Varying Systems","created":"2022-01-14","cited_by_count":2,"area":null},{"id":"2209.09329","title":"MAN: Multi-Action Networks Learning","created":"2022-09-19","cited_by_count":2,"area":null},{"id":"2305.18269","title":"Doing the right thing for the right reason: Evaluating artificial moral cognition by probing cost insensitivity","created":"2023-05-29","cited_by_count":2,"area":null},{"id":"2511.08174","title":"Deep (Predictive) Discounted Counterfactual Regret Minimization","created":"2025-11-11","cited_by_count":1,"area":null},{"id":"2101.01178","title":"Advances in Electron Microscopy with Deep Learning","created":"2021-01-04","cited_by_count":0,"area":null},{"id":"2306.00975","title":"Active Vision Reinforcement Learning under Limited Visual Observability","created":"2023-06-01","cited_by_count":0,"area":null},{"id":"2308.12649","title":"APART: Diverse Skill Discovery using All Pairs with Ascending Reward and DropouT","created":"2023-08-24","cited_by_count":0,"area":null},{"id":"2310.06415","title":"Deep reinforcement learning uncovers processes for separating azeotropic mixtures without prior knowledge","created":"2023-10-10","cited_by_count":0,"area":null},{"id":"2603.19864","title":"NASimJax: A GPU-Accelerated Policy Learning Framework for Penetration Testing","created":"2026-03-20","cited_by_count":0,"area":null},{"id":"2603.29272","title":"MaskAdapt: Learning Flexible Motion Adaptation via Mask-Invariant Prior for Physics-Based Characters","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2609.36802","title":"EasyPPO: Stabilizing the Critic Is Key","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.18186","title":"Reinforcement Learning for Large-Scale Lifelong Multi-Agent Path Finding with Shared Spatial Fields","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}